pm4py.objects.petri_net.stochastic package#

PM4Py – A Process Mining Library for Python

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

Submodules#

pm4py.objects.petri_net.stochastic.obj module#

PM4Py – A Process Mining Library for Python

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

class pm4py.objects.petri_net.stochastic.obj.StochasticPetriNet(name: str = None, places: Collection[Place] = None, transitions: Collection[Transition] = None, arcs: Collection[Arc] = None, properties: Dict[str, Any] = None)[source]#

Bases: PetriNet

class Transition(name: str, label: str = None, in_arcs: Collection[Arc] = None, out_arcs: Collection[Arc] = None, weight: float = 1.0, properties: Dict[str, Any] = None)[source]#

Bases: Transition

property weight: float#

pm4py.objects.petri_net.stochastic.semantics module#

PM4Py – A Process Mining Library for Python

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

class pm4py.objects.petri_net.stochastic.semantics.StochasticPetriNetSemantics[source]#

Bases: PetriNetSemantics[N], Generic[N]

classmethod sample_enabled_transition(pn: N, marking: Counter[P], seed: int = None) → T[source]#

Randomly samples a transition from all enabled transitions

Parameters#

type seed:: int
param pn:: Petri net
param marking:: marking to use

Returns#

return:: a transition sampled from the enabled transitions

classmethod probability_of_transition(pn: N, transition: T, marking: Counter[P]) → float[source]#

Compute the probability of firing a transition in the net and marking.

Args:: pn (N): Stochastic net transition (T): transition to fire marking (Counter[P]): marking to use
Returns:: float: _description_